Quantitative risk analysis of air pollution health effects / Louis Anthony Cox Jr.
Cox, Louis A., Jr. (Louis Anthony), 1957- author.
2021
RA576
Available Online

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Title Quantitative risk analysis of air pollution health effects / Louis Anthony Cox Jr.
Author Cox, Louis A., Jr. (Louis Anthony), 1957- author.
ISBN 9783030573584 (electronic bk.)
3030573583 (electronic bk.)
3030573575
9783030573577
DOI https://doi.org/10.1007/978-3-030-57358-4
Published Cham, Switzerland : Springer, [2021]
Copyright ©2021
Language English
Description 1 online resource
Other Standard Identifiers 10.1007/978-3-030-57358-4 doi
Call Number RA576
Dewey Decimal Classification 363.739/2
Summary This book highlights quantitative risk assessment and modeling methods for assessing health risks caused by air pollution, as well as characterizing and communicating remaining uncertainties. It shows how to apply modern data science, artificial intelligence and machine learning, causal analytics, mathematical modeling, and risk analysis to better quantify human health risks caused by environmental and occupational exposures to air pollutants. The adverse health effects that are caused by air pollution, and preventable by reducing it, instead of merely being statistically associated with exposure to air pollution (and with other many conditions, from cold weather to low income) have proved to be difficult to quantify with high precision and confidence, largely because correlation is not causation. This book shows how to use recent advances in causal analytics and risk analysis to determine more accurately how reducing exposures affects human health risks. Quantitative Risk Analysis of Air Pollution Health Effects is divided into three parts. Part I focuses mainly on quantitative simulation modelling of biological responses to exposures and resulting health risks. It considers occupational risks from asbestos and crystalline silica as examples, showing how dynamic simulation models can provide insights into more effective policies for protecting worker health. Part II examines limitations of regression models and the potential to instead apply machine learning, causal analysis, and Bayesian network learning methods for more accurate quantitative risk assessment, with applications to occupational risks from inhalation exposures. Finally, Part III examines applications to public health risks from air pollution, especially fine particulate matter (PM2.5) air pollution. The book applies freely available browser analytics software and data sets that allow readers to download data and carry out many of the analyses described, in addition to applying the techniques discussed to their own data.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed January 28, 2021).
Series International series in operations research & management science ; 299.
Available in Other Form Print version: 9783030573577
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Part I: Estimating and Simulating Dynamic Health Risks
Chapter 1: Scientific Method for Health Risk Analysis: The Example of Fine Particulate Matter Air Pollution and COVID-19 Mortality Risk
Chapter 2: Modeling Nonlinear Dose-Response Functions: Regression, Simulation, and Causal Bayesian Networks
Chapter 3: Simulating Exposure-Related Health Effects: Basic Ideas
Chapter 4: Case Study: Occupational Health Risks from Crystalline Silica
Chapter 5: Case Study: Health Risks from Asbestos Exposures
Chapter 6: Nonlinear Dose-Time-Response Risk Models for Protecting Worker Health
Part 2: Statistics, Causality, and Machine Learning for Health Risk Assessment
Chapter 7: Why Not Replace Quantitative Risk Assessment Models with Regression Models
Chapter 8: Causal vs. Spurious Spatial Exposure-Response Associations in Health Risk Analysis
Chapter 9: Methods of Causal Analysis for Health Risk Assessment
Chapter 10: Clarifying Exposure-Response Regression Coefficients with Bayesian Networks: Blood Lead-Mortality Associations an Example
Chapter 11: Case Study: Does Molybdenum Decrease Testosterone
Chapter 12: Case Study: Are Low Concentrations of Benzene Disproportionately Dangerous
Part III: Public Health Effects Of Fine Particulate Matter Air Pollution
Chapter 13: Socioeconomic Correlates of Air Pollution and Heart Disease
Chapter 14: How Realistic are Estimates of Health Benefits from Air Pollution Control
Chapter 15: Do Causal Exposure Concentration-Response Relations
Chapter 16: How Do Exposure Estimation Errors Affect Estimated Exposure-Response Relations
Chapter 17: Have Decreases in Air Pollution Reduced Mortality Risks in the United States
Chapter 18: Improving Causal Determination
Chapter 19: Communicating More Clearly about Deaths Caused by Air Pollution.

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